Epidemiologic Features of Recovery From SARS-CoV-2 Infection.

Importance: Persistent symptoms and disability following SARS-CoV-2 infection, known as post-COVID-19 condition or "long COVID," are frequently reported and pose a substantial personal and societal burden. Objective: To determine time to recovery following SARS-CoV-2 infection and identify factors associated with recovery by 90 days. Design, Setting, and Participants: For this prospective cohort study, standardized ascertainment of SARS-CoV-2 infection was conducted starting in April 1, 2020, across 14 ongoing National Institutes of Health-funded cohorts that have enrolled and followed participants since 1971. This report includes data collected through February 28, 2023, on adults aged 18 years or older with self-reported SARS-CoV-2 infection. Exposure: Preinfection health conditions and lifestyle factors assessed before and during the pandemic via prepandemic examinations and pandemic-era questionnaires. Main Outcomes and Measures: Probability of nonrecovery by 90 days and restricted mean recovery times were estimated using Kaplan-Meier curves, and Cox proportional hazards regression was performed to assess multivariable-adjusted associations with recovery by 90 days. Results: Of 4708 participants with self-reported SARS-CoV-2 infection (mean [SD] age, 61.3 [13.8] years; 2952 women [62.7%]), an estimated 22.5% (95% CI, 21.2%-23.7%) did not recover by 90 days post infection. Median (IQR) time to recovery was 20 (8-75) days. By 90 days post infection, there were significant differences in restricted mean recovery time according to sociodemographic, clinical, and lifestyle characteristics, particularly by acute infection severity (outpatient vs critical hospitalization, 32.9 days [95% CI, 31.9-33.9 days] vs 57.6 days [95% CI, 51.9-63.3 days]; log-rank P < .001). Recovery by 90 days post infection was associated with vaccination prior to infection (hazard ratio [HR], 1.30; 95% CI, 1.11-1.51) and infection during the sixth (Omicron variant) vs first wave (HR, 1.25; 95% CI, 1.06-1.49). These associations were mediated by reduced severity of acute infection (33.4% and 17.6%, respectively). Recovery was unfavorably associated with female sex (HR, 0.85; 95% CI, 0.79-0.92) and prepandemic clinical cardiovascular disease (HR, 0.84; 95% CI, 0.71-0.99). No significant multivariable-adjusted associations were observed for age, educational attainment, smoking history, obesity, diabetes, chronic kidney disease, asthma, chronic obstructive pulmonary disease, or elevated depressive symptoms. Results were similar for reinfections. Conclusions and Relevance: In this cohort study, more than 1 in 5 adults did not recover within 3 months of SARS-CoV-2 infection. Recovery within 3 months was less likely in women and those with preexisting cardiovascular disease and more likely in those with COVID-19 vaccination or infection during the Omicron variant wave.

Multimorbidity trajectories in early adulthood and middle age: Findings from the CARDIA prospective cohort study.

Background: Multimorbidity research has focused on the prevalence and consequences of multimorbidity in older populations. Less is known about the accumulation of chronic conditions earlier in the life course. Methods: We identified patterns of longitudinal multimorbidity accumulation using 30 years of data from in-person exams, annual follow-ups, and adjudicated end-points among 4,945 participants of the Coronary Artery Risk Development in Young Adults (CARDIA) study. Chronic conditions included arthritis, asthma, atrial fibrillation, cancer, end stage renal disease, chronic obstructive pulmonary disease, coronary heart disease, diabetes, heart failure, hyperlipidemia, hypertension, and stroke. Trajectory patterns were identified using latent class growth curve models. Results: Mean age (SD) at baseline (1985-6) was 24.9 (3.6), 55% were female, and 51% were Black. The median follow-up was 30 years (interquartile range 25-30). We identified six trajectory classes characterized by when conditions began to accumulate and the rapidity of accumulation: (1) early-fifties, slow, (2) mid-forties, fast, (3) mid-thirties, fast, (4) late-twenties, slow, (5) mid-twenties, slow, and (6) mid-twenties, fast. Compared with participants in the early-fifties, slow trajectory class, participants in mid-twenties, fast were more likely to be female, Black, and currently smoking and had a higher baseline mean waist circumference (83.6 vs. 75.6 cm) and BMI (27.0 vs. 23.4 kg/m2) and lower baseline physical activity (414.1 vs. 442.4 exercise units). Conclusions: A life course approach that recognizes the heterogeneity in patterns of accumulation of chronic conditions from early adulthood into middle age could be helpful for identifying high risk subgroups and developing approaches to delay multimorbidity progression.

Longitudinal associations of screen time, physical activity, and sleep duration with body mass index in U.S. youth.

BACKGROUND: Youth use different forms of screen time (e.g., streaming, gaming) that may be related to body mass index (BMI). Screen time is non-independent from other behaviors, including physical activity and sleep duration. Statistical approaches such as isotemporal substitution or compositional data analysis (CoDA) can model associations between these non-independent behaviors and health outcomes. Few studies have examined different types of screen time, physical activity, and sleep duration simultaneously in relation to BMI. METHODS: Data were baseline (2017-2018) and one-year follow-up (2018-2019) from the Adolescent Brain Cognitive Development Study, a multi-site study of a nationally representative sample of U.S. youth (N = 10,544, mean [SE] baseline age = 9.9 [0.03] years, 48.9% female, 45.4% non-White). Participants reported daily minutes of screen time (streaming, gaming, socializing), physical activity, and sleep. Sex-stratified models estimated the association between baseline behaviors and follow-up BMI z-score, controlling for demographic characteristics, internalizing symptoms, and BMI z-score at baseline. RESULTS: In females, isotemporal substitution models estimated that replacing 30 min of socializing (ß [95% CI] = -0.03 [-0.05, -0.002]), streaming (-0.03 [-0.05, -0.01]), or gaming (-0.03 [-0.06, -0.01]) with 30 min of physical activity was associated with a lower follow-up BMI z-score. In males, replacing 30 min of socializing (-0.03 [-0.05, -0.01]), streaming (-0.02 [-0.03, -0.01]), or gaming (-0.02 [-0.03, -0.01]) with 30 min of sleep was associated with a lower follow-up BMI z-score. In males, replacing 30 min of socializing with 30 min of gaming was associated with a lower follow-up BMI z-score (-0.01 [-0.03, -0.0001]). CoDA estimated that in males, a greater proportion of time spent in baseline socializing, relative to the remaining behaviors, was associated with a higher follow-up BMI z-score (0.05 [0.02, 0.08]). In females, no associations between screen time and BMI were observed using CoDA. CONCLUSIONS: One-year longitudinal associations between screen time and BMI may depend on form of screen time, what behavior it replaces (physical activity or sleep), and participant sex. The alternative statistical approaches yielded somewhat different results. Experimental manipulation of screen time and investigation of biopsychosocial mechanisms underlying the observed sex differences will allow for causal inference and can inform interventions.

Comparison of Cardiovascular Health Profiles Across Population Surveys From 5 High- to Low-Income Countries.

Background: To facilitate the shift from risk-factor management to primordial prevention of cardiovascular disease, the American Heart Association developed guidelines to score and track cardiovascular health (CVH). How the prevalence and trajectories of a high level of CVH across the life course compare among high- and lower-income countries is unknown. Methods: Nationally representative survey data with CVH variables (physical activity, cigarette smoking, body mass index, blood pressure, blood glucose, and total cholesterol levels) were identified in Ethiopia, Bangladesh, Brazil, England, and the US for adults (aged 18-69 years and not pregnant). Data were harmonized, and CVH metrics were scored using the American Heart Association guidelines, as high (2), moderate (1), or low (0), with the prevalence of high scores (better CVH) across the life course compared across countries. Results: Among 28,092 adults (Ethiopia n = 7686, 55.2% male; Bangladesh n = 6731, 48.4% male; Brazil n = 7241, 47.9% male; England n = 2691, 49.5% male, and the US n = 3743, 50.3% male), the prevalence of high CVH scores decreased as country income level increased. Declining CVH with age was universal across countries, but differences were already observable in those aged 18 years. Excess body weight appeared to be the main driver of poor CVH in higher-income countries, and the prevalence of current smoking was highest in Bangladesh. Conclusions: Our findings suggest that CVH decline with age may be universal. Interventions to promote and preserve CVH throughout the life course are needed in all populations, tailored to country-specific time courses of the decline. In countries where the level of CVH remains relatively high, protection of whole societies from risk-factor epidemics may still be feasible.

Contexte: Afin de faciliter la transition de la prise en charge des facteurs de risque vers la prévention primordiale des maladies cardiovasculaires, l'American Heart Association a élaboré des lignes directrices en vue de mesurer la santé cardiovasculaire (SCV) et d'en faire le suivi. On ignore dans quelle mesure la prévalence et la trajectoire d'un niveau élevé de SCV au cours d'une vie se comparent entre les pays à revenu élevé et les pays à plus faible revenu. Méthodologie: Des résultats de sondages représentatifs des pays concernant les variables de la SCV (activité physique, tabagisme, indice de masse corporelle, pression artérielle, glycémie et taux de cholestérol total) ont été obtenus de l'Éthiopie, du Bangladesh, du Brésil, de l'Angleterre et des États-Unis, pour des adultes âgés de 18 à 69 ans, excluant les femmes enceintes. Les données ont été harmonisées, et la SCV a été mesurée conformément aux lignes directrices de l'American Heart Association, et notée en fonction des scores suivants : élevée (2), modérée (1) ou faible (0). La prévalence de scores élevés, soit une meilleure SCV tout au long de la vie, a été comparée entre les pays. Résultats: Parmi 28 092 adultes (Éthiopie, n = 7 686, 55,2 % de sexe masculin; Bangladesh, n = 6 731, 48,4 % de sexe masculin; Brésil, n = 7 241, 47,9 % de sexe masculin; Angleterre, n = 2 691, 49,5 % de sexe masculin, et États-Unis, n = 3 743, 50,3 % de sexe masculin), la prévalence de scores correspondant à une SCV élevée diminuait à mesure que le niveau de revenu du pays augmentait. La diminution de la SCV avec l'âge était universelle dans tous les pays, mais des différences étaient déjà observables chez les personnes âgées de 18 ans. Un surplus de poids corporel semblait être le principal facteur d'une faible SCV dans les pays à revenu plus élevé; la prévalence d'un tabagisme actuel était la plus élevée au Bangladesh. Conclusions: Nos observations laissent croire que le déclin de la SCV avec l'âge pourrait être universel. Il est nécessaire de mener des interventions adaptées à la progression du déclin dans chacun des pays en vue de favoriser et de préserver la SCV tout au long de la vie, et ce, dans toutes les populations. Dans les pays où le niveau de SCV demeure relativement élevé, il pourrait être encore possible de protéger des sociétés entières contre des épidémies liées aux facteurs de risque.

Association Between Young Adult Characteristics and Blood Pressure Trajectories.

BACKGROUND: Blood pressure (BP) trajectories from young adulthood through middle age are associated with cardiovascular risk. We examined the associations of hypertension risk factors with BP trajectories among a large diverse sample. METHODS AND RESULTS: We analyzed data from young adults, aged 18 to 39 years, with untreated BP <140/90 mm Hg at baseline from Kaiser Permanente Southern California (N=355 324). We used latent growth curve models to identify 10-year BP trajectories and to assess the associations between characteristics in young adulthood and BP trajectories. We identified the following 5 distinct systolic BP trajectories, which appeared to be determined mainly by the baseline BP with progressively higher BP at each year: group 1 (lowest BP trajectory, 7.9%), group 2 (26.5%), group 3 (33.0%), group 4 (25.4%), and group 5 (highest BP trajectory, 7.3%). Older age (adjusted odds ratio for 30-39 versus 18-29 years, 1.23 [95% CI, 1.18-1.28]), male sex (13.38 [95% CI, 12.80-13.99]), obesity (body mass index ≥30 versus 18.5-24.9 kg/m2, 14.81 [95% CI, 14.03-15.64]), overweight (body mass index 25-29.9 versus 18.5-24.9 kg/m2, 3.16 [95% CI, 3.00-3.33]), current smoking (1.58 [95% CI, 1.48-1.67]), prediabetes (1.21 [95% CI, 1.13-1.29]), diabetes (1.60 [95% CI, 1.41-1.81]) and high low-density lipoprotein cholesterol (≥160 versus <100 mg/dL, 1.52 [95% CI, 1.37-1.68]) were associated with the highest BP trajectory (group 5) compared with the reference group (group 2). CONCLUSIONS: Traditional hypertension risk factors including smoking, diabetes, and elevated lipids were associated with BP trajectories in young adults, with obesity having the strongest association with the highest BP trajectory group.

Peripheral Blood Mononuclear Cell Gene Expression Associated with Pulmonary Microvascular Perfusion: The Multi-Ethnic Study of Atherosclerosis Chronic Obstructive Pulmonary Disease.

Rationale: Chronic obstructive pulmonary disease (COPD) and emphysema are associated with endothelial damage and altered pulmonary microvascular perfusion. The molecular mechanisms underlying these changes are poorly understood in patients, in part because of the inaccessibility of the pulmonary vasculature. Peripheral blood mononuclear cells (PBMCs) interact with the pulmonary endothelium. Objectives: To test the association between gene expression in PBMCs and pulmonary microvascular perfusion in COPD. Methods: The Multi-Ethnic Study of Atherosclerosis (MESA) COPD Study recruited two independent samples of COPD cases and controls with ⩾10 pack-years of smoking history. In both samples, pulmonary microvascular blood flow, pulmonary microvascular blood volume, and mean transit time were assessed on contrast-enhanced magnetic resonance imaging, and PBMC gene expression was assessed by microarray. Additional replication was performed in a third sample with pulmonary microvascular blood volume measures on contrast-enhanced dual-energy computed tomography. Differential expression analyses were adjusted for age, gender, race/ethnicity, educational attainment, height, weight, smoking status, and pack-years of smoking. Results: The 79 participants in the discovery sample had a mean age of 69 ± 6 years, 44% were female, 25% were non-White, 34% were current smokers, and 66% had COPD. There were large PBMC gene expression signatures associated with pulmonary microvascular perfusion traits, with several replicated in the replication sets with magnetic resonance imaging (n = 47) or dual-energy contrast-enhanced computed tomography (n = 157) measures. Many of the identified genes are involved in inflammatory processes, including nuclear factor-κB and chemokine signaling pathways. Conclusions: PBMC gene expression in nuclear factor-κB, inflammatory, and chemokine signaling pathways was associated with pulmonary microvascular perfusion in COPD, potentially offering new targetable candidates for novel therapies.

Financial strain is associated with poorer cardiovascular health: The multi-ethnic study of atherosclerosis.

Objective: Psychosocial stress is associated with increased cardiovascular disease (CVD) risk. The relationship between financial strain, a toxic form of psychosocial stress, and ideal cardiovascular health (CVH) is not well established. We examined whether financial strain was associated with poorer CVH in a multi-ethnic cohort free of CVD at baseline. Methods: This was a cross-sectional analysis of 6,453 adults aged 45-84 years from the Multi-Ethnic Study of Atherosclerosis. Financial strain was assessed by questionnaire and responses were categorized as yes or no. CVH was measured from 7 metrics (smoking, body mass index, physical activity, diet, total cholesterol, blood glucose and blood pressure). A CVH score of 14 was calculated by assigning points to the categories of each metric (poor = 0 points, intermediate = 1 point, ideal = 2 points). Multinomial logistic regression was used to examine the association of financial strain with the CVH score (inadequate 0-8, average 9-10, and optimal 11-14 points) adjusting for sociodemographic factors, depression and anxiety. Results: The mean age (SD) was 62 (10) and 53 % were women. Financial strain was reported by 25 % of participants. Participants who reported financial strain had lower odds of average (OR, 0.82 [95 % CI, 0.71, 0.94]) and optimal (0.73 [0.62, 0.87]) CVH scores. However, in the fully adjusted model, the association was only significant for optimal CVH scores (0.81, [0.68, 0.97]). Conclusion: Financial strain was associated with poorer CVH. More research is needed to understand this relationship so the burden of CVD can be decreased, particularly among people experiencing financial hardship.

Demographic and Clinical Factors Associated With SARS-CoV-2 Spike 1 Antibody Response Among Vaccinated US Adults: the C4R Study.

This study investigates correlates of anti-S1 antibody response following COVID-19 vaccination in a U.S. population-based meta-cohort of adults participating in longstanding NIH-funded cohort studies. Anti-S1 antibodies were measured from dried blood spots collected between February 2021-August 2022 using Luminex-based microsphere immunoassays. Of 6245 participants, mean age was 73 years (range, 21-100), 58% were female, and 76% were non-Hispanic White. Nearly 52% of participants received the BNT162b2 vaccine and 48% received the mRNA-1273 vaccine. Lower anti-S1 antibody levels are associated with age of 65 years or older, male sex, higher body mass index, smoking, diabetes, COPD and receipt of BNT16b2 vaccine (vs mRNA-1273). Participants with a prior infection, particularly those with a history of hospitalized illness, have higher anti-S1 antibody levels. These results suggest that adults with certain socio-demographic and clinical characteristics may have less robust antibody responses to COVID-19 vaccination and could be prioritized for more frequent re-vaccination.

Incorporating longitudinal history of risk factors into atherosclerotic cardiovascular disease risk prediction using deep learning.

It is increasingly clear that longitudinal risk factor levels and trajectories are related to risk for atherosclerotic cardiovascular disease (ASCVD) above and beyond single measures. Currently used in clinical care, the Pooled Cohort Equations (PCE) are based on regression methods that predict ASCVD risk based on cross-sectional risk factor levels. Deep learning (DL) models have been developed to incorporate longitudinal data for risk prediction but its benefit for ASCVD risk prediction relative to the traditional Pooled Cohort Equations (PCE) remain unknown. Our study included 15,565 participants from four cardiovascular disease cohorts free of baseline ASCVD who were followed for adjudicated ASCVD. Ten-year ASCVD risk was calculated in the training set using our benchmark, the PCE, and a longitudinal DL model, Dynamic-DeepHit. Predictors included those incorporated in the PCE: sex, race, age, total cholesterol, high density lipid cholesterol, systolic and diastolic blood pressure, diabetes, hypertension treatment and smoking. The discrimination and calibration performance of the two models were evaluated in an overall hold-out testing dataset. Of the 15,565 participants in our dataset, 2170 (13.9%) developed ASCVD. The performance of the longitudinal DL model that incorporated 8 years of longitudinal risk factor data improved upon that of the PCE [AUROC: 0.815 (CI 0.782-0.844) vs 0.792 (CI 0.760-0.825)] and the net reclassification index was 0.385. The brier score for the DL model was 0.0514 compared with 0.0542 in the PCE. Incorporating longitudinal risk factors in ASCVD risk prediction using DL can improve model discrimination and calibration.

Incorporating longitudinal history of risk factors into atherosclerotic cardiovascular disease risk prediction using deep learning.

Background: It is increasingly clear that longitudinal risk factor levels and trajectories are related to risk for atherosclerotic cardiovascular disease (ASCVD) above and beyond single measures. Currently used in clinical care, the Pooled Cohort Equations (PCE) are based on regression methods that predict ASCVD risk based on cross-sectional risk factor levels. Deep learning (DL) models have been developed to incorporate longitudinal data for risk prediction but its benefit for ASCVD risk prediction relative to the traditional Pooled Cohort Equations (PCE) remain unknown. Objective: To develop a ASCVD risk prediction model that incorporates longitudinal risk factors using deep learning. Methods: Our study included 15,565 participants from four cardiovascular disease cohorts free of baseline ASCVD who were followed for adjudicated ASCVD. Ten-year ASCVD risk was calculated in the training set using our benchmark, the PCE, and a longitudinal DL model, Dynamic-DeepHit. Predictors included those incorporated in the PCE: sex, race, age, total cholesterol, high density lipid cholesterol, systolic and diastolic blood pressure, diabetes, hypertension treatment and smoking. The discrimination and calibration performance of the two models were evaluated in an overall hold-out testing dataset. Results: Of the 15,565 participants in our dataset, 2,170 (13.9%) developed ASCVD. The performance of the longitudinal DL model that incorporated 8 years of longitudinal risk factor data improved upon that of the PCE [AUROC: 0.815 (CI: 0.782-0.844) vs 0.792 (CI: 0.760-0.825)] and the net reclassification index was 0.385. The brier score for the DL model was 0.0514 compared with 0.0542 in the PCE. Conclusion: Incorporating longitudinal risk factors in ASCVD risk prediction using DL can improve model discrimination and calibration.

Comparison of cardiovascular health profiles across population surveys from five high- to low-income countries.

Aims: With the greatest burden of cardiovascular disease morbidity and mortality increasingly observed in lower-income countries least prepared for this epidemic, focus is widening from risk factor management alone to primordial prevention to maintain high levels of cardiovascular health (CVH) across the life course. To facilitate this, the American Heart Association (AHA) developed CVH scoring guidelines to evaluate and track CVH. We aimed to compare the prevalence and trajectories of high CVH across the life course using nationally representative adult CVH data from five diverse high- to low-income countries. Methods: Surveys with CVH variables (physical activity, cigarette smoking, body mass, blood pressure, blood glucose, and total cholesterol levels) were identified in Ethiopia, Bangladesh, Brazil, England, and the United States (US). Participants were included if they were 18-69y, not pregnant, and had data for these CVH metrics. Comparable data were harmonized and each of the CVH metrics was scored using AHA guidelines as high (2), moderate (1), or low (0) to create total CVH scores with higher scores representing better CVH. High CVH prevalence by age was compared creating country CVH trajectories. Results: The analysis included 28,092 adults (Ethiopia n=7686, 55.2% male; Bangladesh n=6731, 48.4% male; Brazil n=7241, 47.9 % male; England n=2691, 49.5% male, and the US n=3743, 50.3% male). As country income level increased, prevalence of high CVH decreased (>90% in Ethiopia, >68% in Bangladesh and under 65% in the remaining countries). This pattern remained using either five or all six CVH metrics and following exclusion of underweight participants. While a decline in CVH with age was observed for all countries, higher income countries showed lower prevalence of high CVH already by age 18y. Excess body weight appeared the main driver of poor CVH in higher income countries, while current smoking was highest in Bangladesh. Conclusion: Harmonization of nationally representative survey data on CVH trajectories with age in 5 highly diverse countries supports our hypothesis that CVH decline with age may be universal. Interventions to promote and preserve high CVH throughout the life course are needed in all populations, tailored to country-specific time courses of the decline. In countries where CVH remains relatively high, protection of whole societies from risk factor epidemics may still be feasible.

Life Course Cardiovascular Health: Risk Factors, Outcomes, and Interventions.

Since it was first defined by the American Heart Association in 2010, cardiovascular health (CVH) has been extensively studied across the life course. In this review, we present the current literature examining early life predictors of CVH, the later life outcomes of child CVH, and the relatively few interventions which have specifically addressed how to preserve and promote CVH across populations. We find that research on CVH has demonstrated that prenatal and childhood exposures are consistently associated with CVH trajectories from childhood through adulthood. CVH measured at any point in life is strongly predictive of future cardiovascular disease, dementia, cancer, and mortality as well as a variety of other health outcomes. This speaks to the importance of intervening early to prevent the loss of optimal CVH and the accumulation of cardiovascular risk. Interventions to improve CVH are not common but those that have been published most often address multiple modifiable risk factors among individuals within the community. Relatively few interventions have been focused on improving the construct of CVH in children. Future research is needed that will be both effective, scalable, and sustainable. Technology including digital platforms as well as implementation science will play key roles in achieving this vision. In addition, community engagement at all stages of this research is critical. Lastly, prevention strategies that are tailored to the individual and their context may help us achieve the promise of personalized prevention and help promote ideal CVH in childhood and across the life course.

Within-person decline in pregnancy smoking is observable prior to pregnancy awareness: Evidence across two independent observational cohorts.

Decreased consumption of nicotine and other drugs during pregnancy appears to be a cross-species phenomenon from which mechanism(s) capable of interrupting addictive processes could be elucidated. Whether pregnancy influences smoking behaviour independent of women's knowledge of the pregnancy, however, has not been considered. Using repeated measures analysis of variance (ANOVA), we estimated within-person change in mean cigarettes/day smoked across the estimated date of conception but prior to individually reported dates of pregnancy recognition using longitudinal smoking data from two independent observational cohorts, the Growing Up Healthy (GUH, n = 271) and Midwest Infant Development Studies (MIDS, n = 145). Participants smoked an average of half a pack/day in the month immediately before conception (M (SD) = 12(8.1) and 9.5(6.7) cigarettes/day in GUH and MIDS, respectively). We observed within-person declines in smoking after conception, both before (MGUH  = -0.9; 95% CI -1.6, -0.2; p = 0.01; MMIDS  = -1.1; 95% CI -1.9, -0.3; p = 0.01) and after (MGUH  = -4.8; 95% CI -5.5, -4.1; p < 0.001; MMIDS  = -3.3; 95% CI -4.4, -2.5; p < 0.001) women were aware of having conceived, even when women who had quit and women who were planning to conceive were excluded from analyses. Pregnancy may interrupt smoking-related processes via mechanisms not previously considered. Plausible candidates and directions for future research are discussed.

Relative contributions of six lifestyle- and health-related exposures to epigenetic aging: the Coronary Artery Risk Development in Young Adults (CARDIA) Study.

BACKGROUND: DNA methylation-based GrimAge acceleration (GrimAA) is associated with a wide range of age-related health outcomes including cardiovascular disease. Since DNA methylation is modifiable by external and behavioral exposures, it is important to identify which of these exposures may have the strongest contributions to differences in GrimAA, to help guide potential intervention strategies. Here, we assessed the relative contributions of lifestyle- and health-related components, as well as their collective association, to GrimAA. RESULTS: We included 744 participants (391 men and 353 women) from the Coronary Artery Risk Development in Young Adults (CARDIA) study with blood DNA methylation information at CARDIA Exam Year (Y) 20 (2005-2006, mean age 45.9 years). Six cumulative exposures by Y20 were included in the analysis: total packs of cigarettes, total alcohol consumption, education years, healthy diet score, sleep hours, and physical activity. We used quantile-based g-computation (QGC) and Bayesian kernel machine regression (BKMR) methods to assess the relative contribution of each exposure to a single overall association with GrimAA. We also assessed the collective association of the six components combined with GrimAA. Smoking showed the greatest positive contribution to GrimAA, accounting for 83.5% of overall positive associations of the six exposures with GrimAA (QGC weight = 0.835). The posterior inclusion probability (PIP) of smoking also achieved the highest score of 1.0 from BKMR analysis. Healthy diet and education years showed inverse contributions to GrimAA. We observed a U-shaped pattern in the contribution of alcohol consumption to GrimAA. While smoking was the greatest contributor across sex and race subgroups, the relative contributions of other components varied by subgroups. CONCLUSIONS: Smoking, alcohol consumption, and education showed the highest contributions to GrimAA in our study. Higher amounts of smoking and alcohol consumption were likely to contribute to greater GrimAA, whereas achieved education was likely to contribute to lower GrimAA. Identifying pertinent lifestyle- and health-related exposures in a context of collective components can provide direction for intervention strategies and suggests which components should be the primary focus for promoting younger GrimAA.

Status of Cardiovascular Health in US Adults and Children Using the American Heart Association's New "Life's Essential 8" Metrics: Prevalence Estimates From the National Health and Nutrition Examination Survey (NHANES), 2013 Through 2018.

BACKGROUND: The American Heart Association recently published an updated algorithm for quantifying cardiovascular health (CVH)-the Life's Essential 8 score. We quantified US levels of CVH using the new score. METHODS: We included individuals ages 2 through 79 years (not pregnant or institutionalized) who were free of cardiovascular disease from the National Health and Nutrition Examination Surveys in 2013 through 2018. For all participants, we calculated the overall CVH score (range, 0 [lowest] to 100 [highest]), as well as the score for each component of diet, physical activity, nicotine exposure, sleep duration, body mass index, blood lipids, blood glucose, and blood pressure, using published American Heart Association definitions. Sample weights and design were incorporated in calculating prevalence estimates and standard errors using standard survey procedures. CVH scores were assessed across strata of age, sex, race and ethnicity, family income, and depression. RESULTS: There were 23 409 participants, representing 201 728 000 adults and 74 435 000 children. The overall mean CVH score was 64.7 (95% CI, 63.9-65.6) among adults using all 8 metrics and 65.5 (95% CI, 64.4-66.6) for the 3 metrics available (diet, physical activity, and body mass index) among children and adolescents ages 2 through 19 years. For adults, there were significant differences in mean overall CVH scores by sex (women, 67.0; men, 62.5), age (range of mean values, 62.2-68.7), and racial and ethnic group (range, 59.7-68.5). Mean scores were lowest for diet, physical activity, and body mass index metrics. There were large differences in mean scores across demographic groups for diet (range, 23.8-47.7), nicotine exposure (range, 63.1-85.0), blood glucose (range, 65.7-88.1), and blood pressure (range, 49.5-84.0). In children, diet scores were low (mean 40.6) and were progressively lower in higher age groups (from 61.1 at ages 2 through 5 to 28.5 at ages 12 through 19); large differences were also noted in mean physical activity (range, 63.1-88.3) and body mass index (range, 74.4-89.4) scores by sociodemographic group. CONCLUSIONS: The new Life's Essential 8 score helps identify large group and individual differences in CVH. Overall CVH in the US population remains well below optimal levels and there are both broad and targeted opportunities to monitor, preserve, and improve CVH across the life course in individuals and the population.

A novel chronic in vivo oral cadmium exposure-washout mouse model for studying cadmium toxicity and complex diabetogenic effects.

Type II diabetes mellitus (T2DM) is characterized by insulin resistance, ß-cell dysfunction and hyperglycemia. In addition to well known risk factors such as lifestyle and genetic risk score, accumulation of environmental toxicants in organs relevant to glucose metabolism is increasingly recognized as additional risk factors for T2DM. Here, we describe the development of an in vivo oral cadmium (Cd) exposure model. It was shown that oral Cd exposure in drinking water followed by washout and high fat diet (HFD) in C57BL/6N mice results in islet Cd bioaccumulation comparable to that found in native human islets while mitigating the anorexic effects of Cd to achieve the same weight gain required to induce insulin resistance as in Cd naïve control mice. Inter individual variation in plasma glucose and insulin levels as well as islet Cd bioaccumulation was observed in both female and male mice. Regression analysis showed an inverse correlation between islet Cd level and plasma insulin following a glucose challenge in males but not in females. This finding highlights the need to account for inter individual target tissue Cd concentrations when interpreting results from in vivo Cd exposure models. No effect of Cd on insulin secretion was observed in islets ex vivo, highlighting differences between in vivo and ex vivo cadmium exposure models. In summary, our oral in vivo Cd exposure-washout with HFD model resulted in islet Cd bioaccumulation that is relevant in the context of environmental cadmium exposure in humans. Here, we showed that islet Cd bioaccumulation is associated with complex cadmium-mediated changes in glucose clearance and ß-cell function. The model described here will serve as a useful tool to further examine the relationship between Cd exposure, islet Cd bioaccumulation, dysglycemia and their underlying mechanisms.

Development and Validation of a Long-Term Incident Heart Failure Risk Model.

BACKGROUND: Average lifetime risk for heart failure (HF) is high but differs significantly across and within sex-race groups. No models for estimating long-term risk for HF exist, which would allow for earlier identification and interventions in high-risk subsets. The authors aim to derive 30-year HF risk equations. METHODS: Adults between the ages of 20 to 59 years and free of cardiovascular disease at baseline from 5 population-based cohorts were included. Among 24 838 participants (55% women, 25% Black based on self-report), follow-up consisted of 599 551 person-years. Sex- and race-specific 30-year HF risk equations were derived and validated accounting for competing risk of non-HF death. HF was based on a clinical diagnosis. Model discrimination and calibration were assessed using 10-fold cross-validation. Finally, the model was applied to varying risk factor patterns for systematic examination. RESULTS: The rate of incident HF was 4.0 per 1000 person-years. Harrell C statistics were 0.82 (0.80-0.83) and 0.84 (0.82-0.85) in White and Black men and 0.84 (0.82-0.85) and 0.85 (0.83-0.87) in White and Black women, respectively. Hosmer-Lemeshow calibration was acceptable, with χ2 <30 in all subgroups. Risk estimation varied across sex-race groups: for example, in an average 40-year-old nonsmoker with an untreated systolic blood pressure of 140 mm Hg and body mass index of 30 kg/m2, risk was estimated to be 22.8% in a Black man, 13.7% in a White man, 13.0% in a Black woman, and 12.1% in a White woman. CONCLUSIONS: Sex- and race-specific equations for prediction of long-term risk of HF demonstrated high discrimination and adequate calibration.

Cigarette Smoking and Competing Risks for Fatal and Nonfatal Cardiovascular Disease Subtypes Across the Life Course.

Background Cigarette smoking is significantly associated with premature death related and not related to cardiovascular disease (CVD). Whether risk associated with smoking is similar across CVD subtypes and how this translates into years of life lost is not known. Methods and Results We pooled and harmonized individual-level data from 9 population-based cohorts in the United States. All participants were free of clinical CVD at baseline with available data on current smoking status, covariates, and CVD outcomes. We examined the association between smoking status and total CVD and CVD subtypes, including fatal and nonfatal coronary heart disease, stroke, congestive heart failure, and other CVD deaths. We performed (1) modified Kaplan-Meier analysis to estimate long-term risks, (2) adjusted competing Cox models to estimate joint cumulative risks for CVD or noncardiovascular death, and (3) Irwin's restricted mean to estimate years lived free from and with CVD. Of 106 165 adults, 50.4% were women. Overall long-term risks for CVD events were 46.0% (95% CI, 44.7-47.3) and 34.7% (95% CI, 33.3-36.0) in middle-aged men and women, respectively. In middle-aged men who reported smoking compared with those who did not smoke, competing hazard ratios (HRs) were higher for the first presentation being a fatal CVD event (HR, 1.79 [95% CI, 1.68-1.92]), with a similar pattern among women (HR,1.82 [95% CI, 1.68-1.98]). Smoking was associated with earlier CVD onset by 5.1 and 3.8 years in men and women. Similar patterns were observed in younger and older adults. Conclusions Current smoking was associated with a fatal event as the first manifestation of clinical CVD.

Impact of prenatal exposure characterization on early risk detection: Methodologic insights for the HEALthy Brain and Child Development (HBCD) study.

BACKGROUND: A major challenge in prenatal drug exposure research concerns the balance of measurement quality with sample sizes necessary to address confounders. To inform the selection of optimal exposure measures for the HEALthy Brain and Child Development (HBCD) Study, we employed integrated analysis to determine how different methods used to characterize prenatal tobacco exposure influence the detection of exposure-related risk, as reflected in normal variations in birth weight. METHODS: Participants were N = 2323 mother-infant dyads derived from 7 independent developmental cohorts harmonized on measures of exposure, outcome (birthweight), and covariates. We compared estimates of PTE-related effects on birthweight derived from linear regression models when PTE was categorized dichotomously based on any fetal exposure (30% exposed; 69% not exposed); versus categorically, based on common patterns of maternal smoking during pregnancy (never smoked 69%; quit smoking 16%; smoked intermittently 2%; smoked persistently 13%). We secondarily explored sex differences in PTE-birthweight associations across these categorization methods. RESULTS: When PTE was categorized dichotomously, exposure was associated with a - 125-g difference in birthweight (95% C.I. -173.7 - -76.6, p < .0001). When PTE was characterized categorically based on maternal smoking patterns, however, exposure was associated with either no difference in birthweight if mothers quit smoking by the end of the first trimester (B = -30.6, 95% C.I. -88.7-27.4, p = .30); or a - 221.8 g difference in birthweight if mothers did not [95% C.I. (-161.7 to -282.0); p < .001]. Qualitative sex differences were also detected though PTE x sex interactions did not reach statistical significance. Maternal smoking cessation during pregnancy was associated with a 239.3 g increase in birthweight for male infants, and a 114.0 g increase in birthweight for females infants (p = .07). CONCLUSIONS: Categorization of PTE based on patterns of maternal smoking rather than the presence or absence of exposure alone revealed striking nuances in estimates of exposure-related risk. The described method that captures both between-individual and within-individual variability in prenatal drug exposure is optimal and recommended for future developmental investigations such as the HBCD Study.

Race- and Sex-Specific Population Attributable Fractions of Incident Heart Failure: A Population-Based Cohort Study From the Lifetime Risk Pooling Project.

BACKGROUND: Race- and sex-specific differences in heart failure (HF) risk may be related to differential burden and effect of risk factors. We estimated the population attributable fraction (PAF), which incorporates both prevalence and excess risk of HF associated with each risk factor (obesity, hypertension, diabetes, current smoking, and hyperlipidemia), in specific race-sex groups. METHODS: A pooled cohort was created using harmonized data from 6 US longitudinal population-based cohorts. Baseline measurements of risk factors were used to determine prevalence. Relative risk of incident HF was assessed using a piecewise constant hazards model adjusted for age, education, other modifiable risk factors, and the competing risk of death from non-HF causes. Within each race-sex group, PAF of HF was estimated for each risk factor individually and for all risk factors simultaneously. RESULTS: Of 38 028 participants, 55% were female and 22% Black. Hypertension had the highest PAF among Black men (28.3% [95% CI, 18.7%-36.7%]) and women (25.8% [95% CI, 16.3%-34.2%]). In contrast, PAF associated with obesity was the highest in White men (21.0% [95% CI, 14.6%-27.0%]) and women (17.9% [95% CI, 12.8%-22.6%]). Diabetes disproportionately contributed to HF in Black women (PAF, 16.4% [95% CI, 12.7%-19.9%]). The cumulative PAF of all 5 risk factors was the highest in Black women (51.9% [95% CI, 39.3%-61.8%]). CONCLUSIONS: The observed differences in contribution of risk factors across race-sex groups can inform tailored prevention strategies to mitigate disparities in HF burden. This novel competing risk analysis suggests that a sizeable proportion of HF risk may not be associated with modifiable risk factors.